Data Driven Modelling And Predictive Analytics In Business And Finance

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Data-Driven Modelling and Predictive Analytics in Business and Finance

Data-Driven Modelling and Predictive Analytics in Business and Finance
Author :
Publisher : CRC Press
Total Pages : 443
Release :
ISBN-10 : 9781040088463
ISBN-13 : 1040088465
Rating : 4/5 (465 Downloads)

Book Synopsis Data-Driven Modelling and Predictive Analytics in Business and Finance by : Alex Khang

Download or read book Data-Driven Modelling and Predictive Analytics in Business and Finance written by Alex Khang and published by CRC Press. This book was released on 2024-07-24 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data-driven and AI-aided applications are next-generation technologies that can be used to visualize and realize intelligent transactions in finance, banking, and business. These transactions will be enabled by powerful data-driven solutions, IoT technologies, AI-aided techniques, data analytics, and visualization tools. To implement these solutions, frameworks will be needed to support human control of intelligent computing and modern business systems. The power and consistency of data-driven competencies are a critical challenge, and so is developing explainable AI (XAI) to make data-driven transactions transparent. Data- Driven Modelling and Predictive Analytics in Business and Finance covers the need for intelligent business solutions and applications. Explaining how business applications use algorithms and models to bring out the desired results, the book covers: Data-driven modelling Predictive analytics Data analytics and visualization tools AI-aided applications Cybersecurity techniques Cloud computing IoT-enabled systems for developing smart financial systems This book was written for business analysts, financial analysts, scholars, researchers, academics, professionals, and students so they may be able to share and contribute new ideas, methodologies, technologies, approaches, models, frameworks, theories, and practices.


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